Research Publications

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2014
Eilam O., Zarecki R., Oberhardt M., Ursell L.K, Kupiec M., Knight R., Gophna U., Ruppin E..  2014.  Glycan Degradation (GlyDeR) Analysis Predicts Mammalian Gut Microbiota Abundance and Host Diet-Specific Adaptations. mBio. 5(4):e01526-14-e01526-14.
Stempler S, Yizhak K, Ruppin E.  2014.  Integrating Transcriptomics with Metabolic Modeling Predicts Biomarkers and Drug Targets for Alzheimer's Disease. PLoS ONE. 9(8):e105383.
Timp W, Bravo HCorrada, McDonald OG, Goggins M, Umbricht C, Zeiger M, Feinberg AP, Irizarry RA.  2014.  Large hypomethylated blocks as a universal defining epigenetic alteration in human solid tumors.. Genome Med. 6(8):61.
Zarecki R, Oberhardt MA, Yizhak K, Wagner A, Segal EShtifman, Freilich S, Henry CS, Gophna U, Ruppin E.  2014.  Maximal Sum of Metabolic Exchange Fluxes Outperforms Biomass Yield as a Predictor of Growth Rate of Microorganisms. PLoS ONE. 9(5):e98372.
Aryee MJ, Jaffe AE, Corrada-Bravo H, Ladd-Acosta C, Feinberg AP, Hansen KD, Irizarry RA.  2014.  Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays.. Bioinformatics. 30(10):1363-9.
Notebaart R.A, Szappanos B., Kintses B., Pal F., Gyorkei A., Bogos B., Lazar V., Spohn R., Bogos B., Wagner A. et al..  2014.  Network-level architecture and the evolutionary potential of underground metabolism. Proceedings of the National Academy of Sciences. 111(32):11762-11767.
Yizhak K, Gaude E, Le Dévédec S, Waldman YY, Stein GY, van de Water B, Frezza C, Ruppin E.  2014.  Phenotype-based cell-specific metabolic modeling reveals metabolic liabilities of cancer.. Elife. 3
Jerby-Arnon L, Pfetzer N, Waldman YY, McGarry L, James D, Shanks E, Seashore-Ludlow B, Weinstock A, Geiger T, Clemons PA et al..  2014.  Predicting cancer-specific vulnerability via data-driven detection of synthetic lethality.. Cell. 158(5):1199-209.
Khan Z, Wang Y-C, Wieschaus EF, Kaschube M.  2014.  Quantitative 4D analyses of epithelial folding during Drosophila gastrulation.. Development. 141(14):2895-900.
Parker HS, Bravo HCorrada, Leek JT.  2014.  Removing batch effects for prediction problems with frozen surrogate variable analysis.. PeerJ. 2:e561.
Paulson JN, Bravo éctorCorrada, Pop M.  2014.  Reply to: "A fair comparison". Nature Methods. 11(4):359-360.
Akula N., Barb J., Jiang X., Wendland J.R, Choi K.H, Sen S.K, Hou L., Chen D.TW, Laje G., Johnson K. et al..  2014.  RNA-sequencing of the brain transcriptome implicates dysregulation of neuroplasticity, circadian rhythms and GTPase binding in bipolar disorder. Molecular psychiatry.
Akula N, Barb J, Jiang X, Wendland JR, Choi KH, Sen SK, Hou L, Chen DTW, Laje G, Johnson K et al..  2014.  RNA-sequencing of the brain transcriptome implicates dysregulation of neuroplasticity, circadian rhythms and GTPase binding in bipolar disorder.. Mol Psychiatry. 19(11):1179-85.
Patro R, Mount SM, Kingsford C.  2014.  Sailfish enables alignment-free isoform quantification from RNA-seq reads using lightweight algorithms.. Nat Biotechnol. 32(5):462-4.
Molden RC, Goya J, Khan Z, Garcia BA.  2014.  Stable isotope labeling of phosphoproteins for large-scale phosphorylation rate determination.. Mol Cell Proteomics. 13(4):1106-18.
Baeza J, Dowell JA, Smallegan MJ, Fan J, Amador-Noguez D, Khan Z, Denu JM.  2014.  Stoichiometry of site-specific lysine acetylation in an entire proteome.. J Biol Chem. 289(31):21326-38.
Treangen T, Ondov BD, Koren S, Phillippy AM.  2014.  The Harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes. Genome biology. 15:524.
Nguyen N-phuong, Mirarab S, Liu B, Pop M, Warnow T.  2014.  TIPP:Taxonomic Identification and Phylogenetic Profiling. BioinformaticsBioinformatics.
2013
Boca SM, Bravo HCorrada, Caffo B, Leek JT, Parmigiani G.  2013.  A decision-theory approach to interpretable set analysis for high-dimensional data. BiometricsBiometrics. 69
Regier JC, Mitter C, Zwick A, Bazinet AL, Cummings MP, Kawahara AY, Sohn J-C, Zwickl DJ, Cho S, Davis DR et al..  2013.  A large-scale, higher-level, molecular phylogenetic study of the insect order Lepidoptera (moths and butterflies). PLoS OnePLoS One. 8

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